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» Factor analysed hidden Markov models for speech recognition
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INTERSPEECH
2010
14 years 4 months ago
Hidden Markov models with context-sensitive observations for grapheme-to-phoneme conversion
Hidden Markov models (HMMs) have proven useful in various aspects of speech technology from automatic speech recognition through speech synthesis, speech segmentation and grapheme...
Udochukwu Kalu Ogbureke, Peter Cahill, Julie Carso...
ASPDAC
2001
ACM
57views Hardware» more  ASPDAC 2001»
15 years 1 months ago
Speech recognition chip for monosyllables
Abstract-- In the paper, we present a real-time speech recognition chip for monosyllables such as A, B, ..., etc. The chip recognizes up to 64 monosyllables based on the Hidden Mar...
Kazuhiro Nakamura, Qiang Zhu, Shinji Maruoka, Taka...
FTSIG
2007
136views more  FTSIG 2007»
14 years 9 months ago
The Application of Hidden Markov Models in Speech Recognition
Hidden Markov Models (HMMs) provide a simple and effective framework for modelling time-varying spectral vector sequences. As a consequence, almost all present day large vocabula...
Mark J. F. Gales, Steve Young
TSP
2010
14 years 4 months ago
A multi-resolution hidden Markov model using class-specific features
We address the problem in signal classification applications, such as automatic speech recognition (ASR) systems that employ the hidden Markov model (HMM), that it is necessary to...
Paul M. Baggenstoss
ICASSP
2011
IEEE
14 years 1 months ago
Bayesian sensing hidden Markov models for speech recognition
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
George Saon, Jen-Tzung Chien